Is there a common pattern in the age-trajectory of mortality in developed countries at oldest-old ages? Does this pattern, albeit with different parameter values, hold for Medflies, Mexflies, West Indian fruitflies, and Drosophila? Do age trajectories of mortality for males vs. females converge or crossover? How much progress has been made in recent decades in reducing mortality after age 80? This research project is designed to address these questions through theory-based modeling and statistical analysis of data sets that will be rigorously checked for reliability and achieved and published in full to aid future researchers. Specifically, in the proposed research we will: (1) Extend, correct, archive, and publish in full (with public use files) a data set on sex-specific death counts, population counts, and death rates after age 50 and up to the highest ages attained by single year of age, by single year of time for several decades, and when possible, by year of birth, in at least 28 developed countries including the United States. (2) Apply various methods of checking data for reliability, including some innovative Lexis-map methods to these data sets. (3) Refine extinct-cohort methods so that mortality rates can be estimated for not-yet-extinct cohorts based only on death count data. (4) Analyze these data to determine trajectories of mortality over age and time, between sexes, and across countries, with a focus on mortality after age 80 and with emphasis on finding unifying, underlying patterns that aid understanding of the mechanisms of aging and death. (5) Analyze data on Medflies, Mexflies, and West Indian fruitflies with similar questions in mind. (6) Analyze data on Drosophila classified by genotype and by chromosomal markers to determine mortality trajectories for genotypes and for genes (i.e., for populations that share similar chromosomal regions), again with questions in mind similar to those in aim 4, and with the goal of determining whether "inclusive" mortality models can be developed that hold across populations, species, and genotypes.